212.5K
NApart 1 got 900K views. here are more data structure and algorithms visualisation
@nataindata
#Structured Data
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53.2K
JAThe data structure and algorithm goats
@jameelcodes
349.2K
SUComment ‘Projects’ to get 5 Data Scientist Project ideas and a plan 👩🏻💻
♻️ repost to share with friends. Here is how to become a data scientist in 2026 and beyond 📈 the original video was 4 min Andi had to cut it down to 3 because instagram. Should I do a part 3v
what are other skills that you would add to the list and let me know what I should cover in the next video 👩🏻💻
#datascientist #datascience #python #machinelearning #sql #ai
@sundaskhalidd
243.8K
JEComment “project” for my full video that breaks each of these projects down in detail with examples from my own work.
If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude!
Here are the 3 types of projects you need:
↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables
↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one.
↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it
Save this video for later + send to a data friend!
@jessramosdata
375.9K
SWThe best data structures and algorithms resources you need if you’re studying computer science #coding #learntocode #dsa #datastructuresandalgorithms #cs #computerscience #codingforbeginners
@swerikcodes
556.4K
CHThe best projects serve a real use case
Comment “data” for all the links and project descriptions
#tech #data #datascience #ml #explore
@chrisoh.zip
1.0M
GRHow to Learn Data Structures & Algorithms For FREE - AlgoMap #java #software #softwarejobs #softwareengineer #datastructures #leetcode #programming #javadeveloper #datastructuresandalgorithms #python #softwaredeveloper #code #FAANG #coding #javascript #javascriptdeveloper #codingisfun #codinginterview #js #html #css #sql
@greghogg5
1.2M
THHere’s a roadmap to help you go from a software engineer to a data scientist 👩💻 👇
If you’re tired of writing vanilla apps and want to build ML systems instead, this one’s for you.
Step 1 – Learn Python and SQL (not Java, C++, or JavaScript).
→ Focus on pandas, numpy, scikit-learn, matplotlib
→ For SQL: use LeetCode or StrataScratch to practice real-world queries
→ Don’t just write code—learn to think in data
Step 2 – Build your foundation in statistics + math.
→ Start with Practical Statistics for Data Scientists
→ Learn: probability, hypothesis testing, confidence intervals, distributions
→ Brush up on linear algebra (vectors, dot products) and calculus (gradients, chain rule)
Step 3 – Learn ML the right way.
→ Do Andrew Ng’s ML course (Deeplearning.ai)
→ Master the full pipeline: cleaning → feature engineering → modeling → evaluation
→ Read Elements of Statistical Learning or Sutton & Barto if you want to go deeper
Step 4 – Build 2–3 real, messy projects.
→ Don’t follow toy tutorials
→ Use APIs or scrape data, build full pipelines, and deploy using Streamlit or Gradio
→ Upload everything to GitHub with a clear README
Step 5 – Become a storyteller with data.
→ Read Storytelling with Data by Cole Knaflic
→ Learn to explain your findings to non-technical teams
→ Practice communicating precision/recall/F1 in simple language
Step 6 – Stay current. Never stop learning.
→ Follow PapersWithCode (it's now sun-setted, use huggingface.co/papers/trending, ArXiv Sanity, and follow ML practitioners on LinkedIn
→ Join communities, follow researchers, and keep shipping new experiments
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Save this for later.
Tag a friend who’s trying to make the switch.
[software engineer to data scientist, ML career roadmap, python for data science, SQL for ML, statistics for ML, data science career guide, ML project ideas, data storytelling, becoming a data scientist, ML learning path 2025]
@the.datascience.gal
63.7K
VOComment “DATABASE” and I’ll send you the links.
You don’t need expensive courses to understand databases. Some of the best resources for learning database fundamentals, SQL, and system design are completely free.
📌 3 Powerful Resources to Learn Databases & SQL:
1️⃣ Learn SQL Beginner to Advanced – Alex The Analyst
A complete introduction to SQL and working with data. Covers everything from basic queries to joins, aggregations, and real-world data analysis — perfect for beginners.
2️⃣ Databases In-Depth – freeCodeCamp
This goes beyond SQL and teaches how databases actually work. You’ll learn about indexing, transactions, normalization, and performance — the stuff that makes you a better engineer, not just someone who writes queries.
3️⃣ Relational Database Design – freeCodeCamp
Focuses on designing clean and scalable databases. Learn how to structure tables, define relationships, and avoid common design mistakes when building real applications.
These cover everything from querying data to understanding how databases are structured and optimized.
Whether you’re going into backend development, data engineering, or just want to build better projects, learning databases is a must.
Save this post so you can come back to it later — and start building real database knowledge.
@volkan.js
222.8K
CHComment “DATA” for all projects & links!
#coding #datascience #machinelearning #university #student
@chrispathway
741.5K
SWThe best data structures and algorithms resources you need if you’re studying computer science #coding #learntocode #dsa #datastructuresandalgorithms #cs #computerscience #codingforbeginners #usemassive #faang #techjobs
@swerikcodes
4.3K
ADDay 29 : Zero to Hero - SEO in 30 Days: Structured Data
#structureddata #schema #canonicaltags #sitemaps #sitespeed #Schema #seo #linkbuilding #adityakhanna #digitalmarketingtraining #seotraining #freeseotraining #freedigitalmarketingtraining
@adityakhanna_official
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